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Related Concept Videos

Crossover Experiments01:16

Crossover Experiments

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Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
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Randomized Experiments01:13

Randomized Experiments

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
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Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

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Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
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Understanding Treatment Response Heterogeneity Using Crossover Randomized Controlled Trials: A Primer for Exercise

Lorenzo Lolli1, Javi Gonzalez2, Oliver Shannon3

  • 1Department of Sport and Exercise Sciences, Institute of Sport, Manchester Metropolitan University, Manchester, United Kingdom.

International Journal of Sport Nutrition and Exercise Metabolism
|August 28, 2025
PubMed
Summary
This summary is machine-generated.

Crossover randomized controlled trials (RCTs) can reveal treatment response heterogeneity. Replicate crossover RCTs, a type of n-of-1 trial, are crucial for precision medicine by quantifying individual treatment effects.

Keywords:
carryover effectscrossover trialsn-of-1 trialsperson by treatment interactionprecision medicinevariance comparisonvariance componentswashout period

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Area of Science:

  • Exercise and nutrition sciences
  • Biostatistics
  • Precision medicine

Background:

  • Crossover randomized controlled trials (RCTs) are widely used in exercise and nutrition research.
  • These trials are powerful for detecting mean treatment effects.
  • Understanding treatment response heterogeneity is key for personalized medicine.

Purpose of the Study:

  • To review information from crossover RCTs regarding treatment response heterogeneity.
  • To describe variance components underlying observed data in crossover RCTs.
  • To explore the utility of replicate crossover RCTs and n-of-1 trials for precision medicine.

Main Methods:

  • Describing fundamental design issues of crossover RCTs.
  • Quantifying the person-by-treatment variance component using replicate crossover RCTs (multiple cycles).
  • Comparing various data analysis approaches for synthesize findings from six published replicate crossover RCTs.

Main Results:

  • General agreement found between different data analysis approaches for replicate crossover RCTs.
  • A link exists between within-person response consistency and the detection of person-by-treatment interactions.
  • Paired variance comparisons may offer preliminary insights into response heterogeneity but require n-of-1 or replicate crossover RCTs for confirmation.

Conclusions:

  • Multiple-cycle n-of-1 trials and replicate crossover RCTs are underutilized but informative for treatment response heterogeneity.
  • These trial designs are essential components for predicting individual treatment response magnitude.
  • Further research and application of these trial designs are needed to advance personalized treatment strategies.